Use of geostatistical Bayesian updating to integrate airborne radiometrics and soil geochemistry to improve mapping for mineral exploration
JM McKinley, CV Deutsch, C Neufeld, M Patton, M Cooper, ME Young
Mineral exploration programmes around the world use data from remote
sensing, geophysics, and direct sampling. On a regional scale, the
combination of airborne geophysics and ground-based geochemical
sampling can aid geological mapping and mineral exploration. Since
airborne geophysical and traditional soil-sampling data are generated at
different spatial resolutions, they are not immediately comparable due to
their different sampling density. Several geostatistical techniques,
including indicator cokriging and collocated cokriging, can be used to
integrate different types of data into a geostatistical model. However,
with increasing numbers of variables the inference of the crosscovariance
model required for cokriging can be demanding in terms of
effort and computational time. In this paper a Gaussian-based Bayesian
updating approach is applied to integrate airborne radiometric data and
ground-sampled geochemical soil data to maximize information
generated from the soil survey, enabling more accurate geological
interpretation for the exploration and development of natural resources.
The Bayesian updating technique decomposes the collocated estimate
into two models: prior and likelihood models. The prior model is built
from primary information and the likelihood model is built from
secondary information. The prior model is then updated with the
likelihood model to build the final model. The approach allows multiple
secondary variables to be simultaneously integrated into the mapping of
the primary variable. The Bayesian updating approach is demonstrated
using a case study from Northern Ireland. The geostatistical technique
was used to improve the resolution of soil geochemistry, at a density of
one sample per 2 km2, by integrating more closely measured airborne
geophysical data from the GSNI Tellus Survey, measured over a
footprint of 65 x 200 m. The directly measured geochemistry data were
considered as primary data and the airborne radiometric data were used
as secondary data. The approach produced more detailed updated maps
and in particular enhanced information on the mapped distributions of
zinc, copper, and lead. The enhanced delineation of an elongated
northwest/southeast trending zone in the updated maps strengthened
the potential for discovering stratabound base metal deposits.
Keywords: geostatistics, Bayesian updating, airborne geophysics, geochemistry,
mineralization.